In today’s dynamic business landscape, data is the foundation for speed, agility, and transformation. From quick-service restaurants to enterprise software providers, leaders across industries are rethinking how data is managed, accessed, and applied to real-world decisions.

Paul Bruffett, SVP of Enterprise Data and Analytics at Out of the Box Brands, brings a firsthand perspective to this evolution. Having led data strategy across energy, QSR, and technology sectors, he’s seen how a modern data stack — paired with cultural alignment and governance — can unlock powerful outcomes. Whether enabling real-time decision-making in the field or embedding generative AI into daily workflows, Bruffett believes the next frontier isn’t just about collecting more data — it’s about enabling more people to use it.

In this conversation, Bruffett shares lessons from the front lines of enterprise data transformation: why data democratization still matters, how genAI is quietly reshaping reporting and operations, and what retail and food service leaders should be doing now to stay ahead.

Redefining data democratization: From dashboards to decision-making

Data democratization has long been an aspirational goal in enterprise strategy — but as Bruffett notes, achieving it takes more than just talk. It requires the right architecture, the right tools, and above all, a cultural commitment to putting data in the hands of those closest to the business.

At Devon Energy, Bruffett saw data democratization in action. By pairing modern data platforms like Snowflake and Databricks with automated data integration and replication technologies, the team was able to make real-time data widely accessible. Business units were empowered to generate insights on their own, many of which were scalable across the broader organization. This bottom-up approach worked because the people closest to the business challenges had the clearest understanding of what insights were needed — and how best to act on them.

Employees were given direct access to real-time data, along with the tools to build their own models and workflows — from SQL in Snowflake to machine learning models in Databricks. It wasn’t just about visibility. It was about enabling action.

Now, at Out of the Box Brands, Bruffett is focused on recreating that continuum. Central to that effort is a modern data movement stack — one that gives teams access to raw data without upfront curation that limits future use cases.

Rethinking the role of genAI in everyday decision-making

As organizations continue to explore the value of genAI, a growing number of leaders are beginning to view it not as a standalone solution, but as an embedded feature that quietly enhances the tools teams already use. One prominent example Bruffett sees is the use of genAI to allow users of BI tools to interact with dashboards conversationally. This shift is particularly impactful for stakeholders who don’t have the technical expertise to write queries or interpret complex datasets, yet still need fast, meaningful answers to business questions.

GenAI has enormous potential in both the reporting and data layers. Whether it’s helping a frontline manager understand sales anomalies or guiding a marketer through year-over-year trends, genAI can act as a first responder to ad hoc questions, surfacing context and insights in real time. This not only reduces the load on data teams but accelerates time-to-decision across a business.

Crucially, Bruffett views genAI as a powerful catalyst for furthering data democratization. GenAI can bridge gaps by enabling open-ended, natural language interactions with data — even unstructured data like strategy documents or market intel — reducing the friction required to extract value from enterprise data assets.

The end goal is to develop a published layer of curated, trusted data products that anyone in the organization can interrogate intuitively, broadening access to insights and empowering teams to make better decisions, faster.

Navigating the future of QSR and retail: Automation, personalization, and data readiness

As the retail and food and beverage industries evolve, the most impactful trends are not necessarily new — they're accelerations of existing shifts. According to Bruffett, today’s data leaders should focus not on anticipating entirely new disruptors, but on preparing their organizations to capitalize on the momentum already building across automation, digital transformation, and data-driven personalization.

Cost pressures remain a constant challenge, and automation continues to be a key solution. From self-service kiosks in restaurants to automated supply chain systems, organizations are deploying technology not only to reduce overhead, but also to improve customer experience. For instance, kiosks offer guests more time to browse and interact with digital menus, often resulting in higher order values. More importantly, these tools free up in-store staff to focus on food quality and face-to-face service, reinforcing hospitality rather than replacing it.

The shift to automation also sets the stage for more intelligent, responsive customer engagement. Bruffett notes that while many quick service restaurants (QSRs) historically lacked deep customer data, loyalty programs are now starting to change that. As brands like Starbucks lead the way in digital engagement, others in the industry are moving rapidly to catch up — integrating machine learning and decision intelligence into their core operations.

Looking ahead, Bruffett anticipates the continued blending of physical and digital channels. With many QSRs now targeting 20% or more of their sales through digital platforms, the industry is quickly transitioning from traditional service models to more omnichannel, data-informed strategies. This shift requires more than just technology — it demands well-governed data infrastructure capable of powering real-time personalization at scale.

For data leaders across retail and food and beverage, the takeaway is clear: prioritize systems and processes that enable both automation and agility. As businesses grow more digital, the ability to adapt quickly — and personalize meaningfully — will define the next wave of competitive advantage.

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